Landing Page & Referral System

Bettafi is a UK personal-finance app that securely connects to a user's banks and turns the resulting transaction data into AI-driven, plain-English next steps for budgeting, debt management and savings. The product itself is sophisticated — pre-launch, the conversion problem was the opposite. A new fintech entering an already-crowded UK market needed a launch presence that did three jobs at once: explain the product clearly enough that a sceptical visitor would trust it with their bank credentials, sign up enough early-access users to validate the proposition before opening to general availability, and turn each of those signups into a recruiter for the next.

Off-the-shelf waitlist tools (Prefinery, ViralLoops, Loops Forms) were considered and rejected. They handle the mechanic, but every page they produce is recognisably a third-party widget. For a brand whose entire pitch is *trust me with your bank logins*, the launch experience needed to feel native, owned, and on-brand from the first frame onward — not an embed living inside a stock template.

The full launch experience shipped together — a custom Next.js landing page, a server-driven referral and waitlist system with attribution, an early-access form integrated to Bettafi's stack, and a confirmation-and-share flow that doubles as an acquisition surface. The result is a launch presence that feels native to the product rather than parented out to a SaaS form provider, and a referral mechanic that turns each signup into a small acquisition channel without bolting on a separate platform.

Beyond the initial launch, the same landing page and referral surface continue to serve as Bettafi's primary acquisition page during early access — the architecture was deliberately set up so copy, screenshots and the referral reward mechanic can be iterated by the Bettafi team without touching the underlying infrastructure. The visual system carries through cleanly to social, email and out-of-product touchpoints, and the referral system has scaled as expected without manual intervention as waiting-list volume has grown.